PMut: a web-based tool for the annotation of pathological variants on proteins, 2017 update

Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants

The present limitations in the pathogenicity prediction of BRCA1 and BRCA2 (BRCA1/2) missense variants constitute an important problem with negative consequences for the diagnosis of hereditary breast and ovarian cancer. However, it has been proposed that the use of endophenotype predictions, i.e., computational estimates of the outcomes of functional assays, can be a good option to address this bottleneck. The application of this idea to the BRCA1/2 variants in the CAGI 5-ENIGMA international challenge has shown promising results. Here, we developed this approach, exploring the predictive performances of the regression models applied to the BRCA1/2 variants for which the values of the homology-directed DNA repair and saturation genome editing assays are available. Our results first showed that we can generate endophenotype estimates using a few molecular-level properties. Second, we show that the accuracy of these estimates is enough to obtain pathogenicity predictions comparable to those of many standard tools. Third, endophenotype-based predictions are complementary to, but do not outperform, those of a Random Forest model trained using variant pathogenicity annotations instead of endophenotype values. In summary, our results confirmed the usefulness of the endophenotype approach for the pathogenicity prediction of the BRCA1/2 missense variants, suggesting different options for future improvements.

Comparative analysis of the superoxide dismutase gene family in Cetartiodactyla

Cetacea, whales, dolphins and porpoises form an order of mammals adapted to aquatic life. Their transition to an aquatic habitat resulted in exceptional protection against cellular insults, including oxidative and osmotic stress. Here, we considered the structure and molecular evolution of the superoxide dismutase (SOD) gene family, which encodes essential enzymes in the mammalian antioxidant system, in the superorder Cetartiodactyla. To this end, we juxtaposed cetaceans and their closest extant relatives (order Artiodactyla). We identified 94 genes in 23 species, of which 70 are bona fide intact genes. Although the SOD gene family is conserved in Cetartiodactyla, lineage-specific gene duplications and deletions were observed. Phylogenetic analyses show that the SOD2 subfamily diverged from a clade containing SOD1 and SOD3, suggesting that cytoplasmic, extracellular and mitochondrial SODs have started down independent evolutionary paths. Specific-amino acid changes (e.g. K130N in SOD2) that may enhance ROS elimination were identified in cetaceans. In silico analysis suggests that the core transcription factor repertoire of cetartiodactyl SOD genes may include Sp1, NF-κB, Nrf2 and AHR. Putative transcription factors binding sites responding to hypoxia were (e.g. Suppressor of Hairless; Su(H)) found in the cetacean SOD1 gene. We found significant evidence for positive selection in cetaceans using codon models. Cetaceans with different diving abilities also show divergent evolution of SOD1 and SOD2. Our genome-wide analysis of SOD genes helps clarify their relationship and evolutionary trajectory and identify putative functional changes in cetaceans.

Computational Studies of the Structural Basis of Human RPS19 Mutations Associated With Diamond-Blackfan Anemia

Diamond-Blackfan Anemia (DBA) is an inherited rare disease characterized with severe pure red cell aplasia, and it is caused by the defective ribosome biogenesis stemming from the impairment of ribosomal proteins. Among all DBA-associated ribosomal proteins, RPS19 affects most patients and carries most DBA mutations. Revealing how these mutations lead to the impairment of RPS19 is highly demanded for understanding the pathogenesis of DBA, but a systematic study is currently lacking. In this work, based on the complex structure of human ribosome, we comprehensively studied the structural basis of DBA mutations of RPS19 by using computational methods. Main structure elements and five conserved surface patches involved in RPS19-18S rRNA interaction were identified. We further revealed that DBA mutations would destabilize RPS19 through disrupting the hydrophobic core or breaking the helix, or perturb the RPS19-18S rRNA interaction through destroying hydrogen bonds, introducing steric hindrance effect, or altering surface electrostatic property at the interface. Moreover, we trained a machine-learning model to predict the pathogenicity of all possible RPS19 mutations. Our work has laid a foundation for revealing the pathogenesis of DBA from the structural perspective.

Structural genomics approach to investigate deleterious impact of nsSNPs in conserved telomere maintenance component 1

Conserved telomere maintenance component 1 (CTC1) is an important component of the CST (CTC1-STN1-TEN1) complex, involved in maintaining the stability of telomeric DNA. Several non-synonymous single-nucleotide polymorphisms (nsSNPs) in CTC1 have been reported to cause Coats plus syndrome and Dyskeratosis congenital diseases. Here, we have performed sequence and structure analyses of nsSNPs of CTC1 using state-of-the-art computational methods. The structure-based study focuses on the C-terminal OB-fold region of CTC1. There are 11 pathogenic mutations identified, and detailed structural analyses were performed. These mutations cause a significant disruption of noncovalent interactions, which may be a possible reason for CTC1 instability and consequent diseases. To see the impact of such mutations on the protein conformation, all-atom molecular dynamics (MD) simulations of CTC1-wild-type (WT) and two of the selected mutations, R806C and R806L for 200 ns, were carried out. A significant conformational change in the structure of the R806C mutant was observed. This study provides a valuable direction to understand the molecular basis of CTC1 dysfunction in disease progression, including Coats plus syndrome.

Crystallographic modeling of the PNPT1:c.1453A>G variant as a cause of mitochondrial dysfunction and autosomal recessive deafness; expanding the neuroimaging and clinical features

Deficiency of the proteins involved in oxidative phosphorylation (OXPHOS) can lead to mitochondrial dysfunction. Polyribonucleotide nucleotidyltransferase 1 (PNPT1) is one of the genes involved in the OXPHOS and encodes the mitochondrial polynucleotide phosphorylase (PNPase) which is implicated in RNA-processing exoribonuclease activity. Herein, we report a 34-month-old boy who presented with global developmental delay, muscular hypotonia, hearing impairment, and movement disorders including chorea and dystonia. Mitochondrial genome sequencing and whole-exome sequencing (WES) were performed and a variant in PNPT1:c.1453A>G; p. (Met485Val) was identified. A number of patient's neurologic problems had been already reported in previous studies, however, lower limbs spasticity and bulbar dysfunction were novel phenotypic findings. In addition, delayed myelination during infancy, progressive basal ganglia atrophy, and brain stem abnormal signals including transverse pontine fibers and superior colliculus involvement were also novel neuroimaging findings in this case. Different crystallographic modeling and stereochemical analysis of the c.1453A>G; p. (Met485Val) variant showed this variant affects the active site of the protein and disrupts the normal protein function.

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.

Molecular characterisation of rare loss-of-function NPAS3 and NPAS4 variants identified in individuals with neurodevelopmental disorders

Aberrations in the excitatory/inhibitory balance within the brain have been associated with both intellectual disability (ID) and schizophrenia (SZ). The bHLH-PAS transcription factors NPAS3 and NPAS4 have been implicated in controlling the excitatory/inhibitory balance, and targeted disruption of either gene in mice results in a phenotype resembling ID and SZ. However, there are few human variants in NPAS3 and none in NPAS4 that have been associated with schizophrenia or neurodevelopmental disorders. From a clinical exome sequencing database we identified three NPAS3 variants and four NPAS4 variants that could potentially disrupt protein function in individuals with either developmental delay or ID. The transcriptional activity of the variants when partnered with either ARNT or ARNT2 was assessed by reporter gene activity and it was found that variants which truncated the NPAS3/4 protein resulted in a complete loss of transcriptional activity. The ability of loss-of-function variants to heterodimerise with neuronally enriched partner protein ARNT2 was then determined by co-immunoprecipitation experiments. It was determined that the mechanism for the observed loss of function was the inability of the truncated NPAS3/4 protein to heterodimerise with ARNT2. This further establishes NPAS3 and NPAS4 as candidate neurodevelopmental disorder genes.

IDRMutPred: predicting disease-associated germline nonsynonymous single nucleotide variants (nsSNVs) in intrinsically disordered regions

Motivation

Despite of the lack of folded structure, intrinsically disordered regions (IDRs) of proteins play versatile roles in various biological processes, and many nonsynonymous single nucleotide variants (nsSNVs) in IDRs are associated with human diseases. The continuous accumulation of nsSNVs resulted from the wide application of NGS has driven the development of disease-association prediction methods for decades. However, their performance on nsSNVs in IDRs remains inferior, possibly due to the domination of nsSNVs from structured regions in training data. Therefore, it is highly demanding to build a disease-association predictor specifically for nsSNVs in IDRs with better performance.

Results

We present IDRMutPred, a machine learning-based tool specifically for predicting disease-associated germline nsSNVs in IDRs. Based on 17 selected optimal features that are extracted from sequence alignments, protein annotations, hydrophobicity indices and disorder scores, IDRMutPred was trained using three ensemble learning algorithms on the training dataset containing only IDR nsSNVs. The evaluation on the two testing datasets shows that all the three prediction models outperform 17 other popular general predictors significantly, achieving the ACC between 0.856 and 0.868 and MCC between 0.713 and 0.737. IDRMutPred will prioritize disease-associated IDR germline nsSNVs more reliably than general predictors.

Availability and implementation

The software is freely available at http://www.wdspdb.com/IDRMutPred.

Supplementary information

Supplementary data are available at Bioinformatics online.

Computational Analysis Indicates That PARP1 Acts as a Histone Deacetylases Interactor Sharing Common Lysine Residues for Acetylation, Ubiquitination, and SUMOylation in Alzheimer's and Parkinson's Disease

Aim/Hypothesis : Lysine residues are known for the post-translational modifications (PTMs) such as acetylation, ubiquitination, and SUMOylation. In acetylation, histone deacetylase (HDAC) and its interactors cause transcriptional deregulation and cause mitochondrial dysfunction, apoptosis, inflammatory response, and cell-cycle impairment that cause brain homeostasis and neuronal cell death. Other regulatory PTMs involved in the pathogenesis of neurodegenerative diseases (NDDs) are ubiquitination and SUMOylation for the degradation of the misfolded proteins. Thus, we aim to investigate the potential acetylation/ubiquitination/SUMOylation crosstalk sites in the HDAC interactors, which cause NDDs. Furthermore, we aim to identify the influence of PTMs on the structural features of proteins and the impact of putative lysine mutation on disease susceptibility. Last, we aim to examine the impact of the putative mutation on acetylated lysine for ubiquitination and SUMOylation. Results : Herein, we integrate 1455 genes, 3094 genes, and 1940 genes related to HDAC interactors, Alzheimer's disease (AD), and Parkinson's disease (PD), respectively. Furthermore, the protein-protein interaction and PTM integrations from different databases identified 32 proteins that are associated with HDAC, AD, and PD with 1489 potential lysine-modified sites. HDAC interactors poly(ADP-ribose) polymerase 1 (PARP1), nucleophosmin (NPM1), and cyclin-dependent kinase 1 (CDK1) involved in the progression of NDDs and 64 and 75% of PTM sites in PARP1, NPM1, and CDK1 fall into coiled and ordered regions, respectively. Moreover, 15 putative lysine sites have been found in the crosstalk and K148, K249, K528, K637, K700, and K796 of PARP1 are crosstalk hotspots. Conclusion : The loss of acetylated hotspot sites results in the loss of ubiquitination and SUMOylation function on nearby sites, which is relatively higher when compared to the gain of function.

Novel SCN5A variants identified in a group of Iranian Brugada syndrome patients

Brugada syndrome (BrS) is a rare hereditary arrhythmia syndrome that increases an individual's risk for sudden cardiac death (SCD) due to ventricular fibrillation. This disorder is regarded as a notable cause of death in individuals aged less than 40 years, responsible for up to 40% of sudden deaths in cases without structural heart disease, and is reported to be an endemic in Asian countries. Mutations in SCN5A are found in approximately 30% of patients with Brugada syndrome. This study aimed to investigate mutations in the SCN5A gene in a group of Iranian Brugada syndrome patients. Nine probands (n = 9, male, mean age = 39) diagnosed with Brugada syndrome were enrolled in this study. Exon 2 to 29 were amplified by PCR and subjected to direct sequencing. Eight in silico prediction tools were used to anticipate the effects of non-synonymous variants. Seven known polymorphisms and 2 previously reported disease-causing mutations, including H558R and G1406R, were found in the studied cases. Twenty novel variants were identified: 15 missense, 2 frameshift, 2 synonymous, and one nonsense variants. In silico tools predicted 11 non-synonymous variants to have damaging effects, whereas frameshift and nonsense variants were considered inherently pathogenic. The novel variants identified in this study, alongside previously reported mutations, are highly likely to be the cause of the Brugada syndrome phenotype observed in the patient group. Further analysis is required to understand the physiological effects caused by these variants.

Alkaptonuria in Russia: mutational spectrum and novel variants

Alkaptonuria is a rare genetic disease caused by mutations in HGD gene. Here we report the results of genetic and biochemical analysis of 49 Russian patients with alkaptonuria. One of the common variants c.481G > A; p.(Gly161Arg) comprising 72.4% of identified alleles was found in 45 of 49 patients in our cohort, which is probably the highest frequency of this variant worldwide. 9 novel variants were found: 6 missense, 2 splicing and 1 loss of start-codon. For missense variants we performed bioinformatic analysis, protein 3D-modeling and molecular dynamics simulations, which strongly suggest their pathogenic effect. For the rare synonymous variant c.753C > T; p.(Gly251Gly), which was found in 3 cases and predicted to activate cryptic splice site, we performed the detailed functional analysis on patient's cDNA and minigene assay and confirmed its pathogenicity.

Long-QT founder variant T309I-Kv7.1 with dominant negative pattern may predispose delayed afterdepolarizations under β-adrenergic stimulation

The variant c.926C > T (p.T309I) in KCNQ1 gene was identified in 10 putatively unrelated Czech families with long QT syndrome (LQTS). Mutation carriers (24 heterozygous individuals) were more symptomatic compared to their non-affected relatives (17 individuals). The carriers showed a mild LQTS phenotype including a longer QTc interval at rest (466 ± 24 ms vs. 418 ± 20 ms) and after exercise (508 ± 32 ms vs. 417 ± 24 ms), 4 syncopes and 2 aborted cardiac arrests. The same haplotype associated with the c.926C > T variant was identified in all probands. Using the whole cell patch clamp technique and confocal microscopy, a complete loss of channel function was revealed in the homozygous setting, caused by an impaired channel trafficking. Dominant negativity with preserved reactivity to β-adrenergic stimulation was apparent in the heterozygous setting. In simulations on a human ventricular cell model, the dysfunction resulted in delayed afterdepolarizations (DADs) and premature action potentials under β-adrenergic stimulation that could be prevented by a slight inhibition of calcium current. We conclude that the KCNQ1 variant c.926C > T is the first identified LQTS-related founder mutation in Central Europe. The dominant negative channel dysfunction may lead to DADs under β-adrenergic stimulation. Inhibition of calcium current could be possible therapeutic strategy in LQTS1 patients refractory to β-blocker therapy.

Molecular dynamics, residue network analysis, and cross-correlation matrix to characterize the deleterious missense mutations in GALE causing galactosemia III

Epimerase-deficiency galactosemia (EDG) is caused by mutations in the UDP-galactose 4'-epimerase enzyme, encoded by gene GALE. Catalyzing the last reaction in the Leloir pathway, UDP-galactose-4-epimerase catalyzes the interconversion of UDP-galactose and UDP-glucose. This study aimed to use in-depth computational strategies to prioritize the pathogenic missense mutations in GALE protein and investigate the systemic behavior, conformational spaces, atomic motions, and cross-correlation matrix of the GALE protein. We searched four databases (dbSNP, ClinVar, UniProt, and HGMD) and major biological literature databases (PubMed, Science Direct, and Google Scholar), for missense mutations that are associated with EDG patients, our search yielded 190 missense mutations. We applied a systematic computational prediction pipeline, including pathogenicity, stability, biochemical, conservational, protein residue contacts, and structural analysis, to predict the pathogenicity of these mutations. We found three mutations (p.K161N, p.R239W, and p.G302D) with a severe phenotype in patients with EDG that correlated with our computational prediction analysis; thus, they were selected for further structural and simulation analyses to compute the flexibility and stability of the mutant GALE proteins. The three mutants were subjected to molecular dynamics simulation (MDS) with native protein for 200 ns using GROMACS. The MDS demonstrated that these mutations affected the beta-sheets and helical region that are responsible for the catalytic activity; subsequently, affects the stability and flexibility of the mutant proteins along with a decrease and more deviations in compactness when compared to that of a native. Also, three mutations created major variations in the combined atomic motions of the catalytic and C-terminal regions. The network analysis of the residues in the native and three mutant protein structures showed disturbed residue contacts occurred owing to the missense mutations. Our findings help to understand the structural behavior of a protein owing to mutation and are intended to serve as a platform for prioritizing mutations, which could be potential targets for drug discovery and development of targeted therapeutics.

Differential genotypic signatures of Toll-like receptor polymorphisms among dengue-chikungunya mono- and co-infected Eastern Indian patients

Dengue (DENV) and chikungunya (CHIKV) viral infections trigger high patient morbidity and mortality. Mono-/co-infection of these viruses activates innate immune response, triggering Toll-like receptor (TLR) pathways. The present study investigated the differential role of TLR3, 7 and 8 single-nucleotide polymorphisms (SNPs) between mono- and co-infected Eastern Indian patients. Interaction of TLR polymorphic variants with signal peptidase complex (SPC18) was explored which might affect immune signalling against DENV/CHIKV infections. Out of 550 febrile symptomatic patients, 128 DENV-CHIKV co-infected samples were genotyped for eight SNPs of TLR3 (rs3775290-chr4:186083063), TLR7 (rs179008-chrX:12885540, rs5741880-chrX:12869297, rs179010-chrX:12884766, rs3853839-chrX:12889539) and TLR8 (rs5744080-chrX:12919685, rs3764879-chrX:12906578, rs3764880-chrX:12906707) by PCR-RFLP along with 157 healthy individuals. Statistical analysis established genotypic association of TLR SNPs with DENV-CHIKV co-infection, and difference between mono- and co-infected patients and their role in determining high viral load (HVL) during competitive viral replication among co-infected patients. In silico protein-protein docking evaluated interactive effect of TLR variants with SPC18. The findings revealed patients with CC genotypes of TLR7 and 8 SNPs were significantly susceptible towards co-infection, whereas specific genotypes of TLR7 and 8 imparted protection against co-infection. Differential analysis between mono-/co-infected patients revealed distinct genotypic distribution of TLR3, 7 and 8 SNPs. Co-infected patients with TT-rs179010 exhibited DENV-HVL, whereas CHIKV-HVL was detected among patients with other genotypes. Molecular docking of TLR7-rs179008 Q variant and TLR8-rs3764880 V variant with SPC18 generated better free binding energy. This study underlined the importance of TLR7 and 8 SNPs towards mono-/co-infection of DENV/CHIKV, with certain genotypes associated with co-infection susceptibility. Moreover, it suggested a probable role of specific genotypes of TLR7 and 8 polymorphisms imparting high dengue/chikungunya viral load among co-infected patients.

Mitochondrial DNA maintenance disorders in 102 patients from different parts of Russia: Mutational spectrum and phenotypes

Currently, pathogenic variants in more than 25 nuclear genes, involved in mtDNA maintenance, are associated with human disorders. mtDNA maintenance disorders manifest with a wide range of phenotypes, from severe infantile-onset forms of myocerebrohepatopathy to late-onset forms of myopathies, chronic progressive external ophthalmoplegia, and parkinsonism. This study represents the results of molecular genetic analysis and phenotypes of 102 probands with mtDNA maintenance disorders. So far, this is the largest Russian cohort for this group of diseases. Mutations were identified in 10 mtDNA maintenance genes: POLG (n = 59), DGUOK (n = 14), TWNK (n = 14), TK2 (n = 8), MPV17 (n = 2), OPA3 (n = 1), FBXL4 (n = 1), RRM2B (n = 1), SUCLG1 (n = 1) and TYMP (n = 1). We review a mutation spectrum for the DGUOK and TWNK genes, that can be specific for the Russian population. In 34 patients we measured the blood mtDNA copy number and showed its significant reduction. Novel variants were found in 41 cases, which significantly expands the mutational landscape of mtDNA maintenance disorders.

Transcription-translation error: In-silico investigation of the structural and functional impact of deleterious single nucleotide polymorphisms in GULP1 gene

Nonsynonymous single nucleotide polymorphisms (nsSNPs) are one of the most common forms of mutations known to disrupt the product of translation thereby altering the protein structure-function relationship. GULP1 (PTB domain-containing engulfment adaptor protein 1) is an evolutionarily conserved adaptor protein that has been associated with glycated hemoglobin (HbA1c) in Genome-Wide Association Studies (GWAS). In order to understand the role of GULP1 in the etiology of diabetes, it is important to study some functional nsSNPs present within the GULP1 protein. We, therefore, used a SNPinformatics approach to retrieve, classify, and determine the stability effect of some nsSNPs. Y27C, G142D, A144T, and Y149C were jointly predicted by the pathogenic-classifying tools to be disease-causing, however, only G142D, A144T, and Y149C had their structural architecture perturbed as predicted by I-MUTANT and MuPro. Interestingly, G142D and Y149C occur at positions 142 and 149 of GULP1 which coincidentally are found within the binding site of GULP1. Protein-Protein interaction analysis also revealed that GULP1 interacted with 10 proteins such as Cell division cycle 5-like protein (CDC5L), ADP-ribosylation factor 6 (ARF6), Arf-GAP with coiled-coil (ACAP1), and Multiple epidermal growth factor-like domains protein 10 (MEGF10), etc. Taken together, rs1357922096, rs1264999716, and rs128246649 could be used as genetic biomarkers for the diagnosis of diabetes. However, being a computational study, these nsSNPs require experimental validation to explore their metabolic involvement in the pathogenesis of diseases.

BRCA1 and BRCA2 truncating mutations and variants of unknown significance in Egyptian female breast cancer patients

BACKGROUND

Breast cancer is the most common malignancy among women worldwide and the leading cause of cancer death in economically developing countries. We sought to study the contribution of BRCA1/2 mutations to the burden of breast cancer in Egypt.

PATIENTS AND METHODS

103 Egyptian female breast cancer patients, unselected for age of onset or family history, were included in the study. Mutational screening of some exons of BRCA1/2 genes was performed using High Resolution Melting analysis followed by direct sequencing of detected variants.

RESULTS

Twenty sequence variants were identified. According to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines, 8 variants were classified as pathogenic (Class 5), 1 as likely pathogenic and 11 as variants of unknown significance (Class 3). The pathogenic variants comprised 5 novel frameshift mutations; BRCA1 c.5205delA and BRCA2 (c.3641delT, c.3291dupT, c.3292delA, and c.787dupA) mutations; 1 novel nonsense mutation (BRCA2 c.3280A>T) and 2 previously described missense mutations (BRCA1 c.117T>G, c.110C>A).

CONCLUSION

This study provides the results of our attempt to delineate the genetic aspect of breast cancer among the Egyptian population and emphasizes the necessity of implementing screening strategies for early diagnosis and counseling for breast cancer in Egypt.

Peroxisome proliferator-activated receptor α as a novel therapeutic target for schizophrenia

BACKGROUND

The pathophysiology of schizophrenia, a major psychiatric disorder, remains elusive. In this study, the role of peroxisome proliferator-activated receptor (PPAR)/retinoid X receptor (RXR) families, belonging to the ligand-activated nuclear receptor superfamily, in schizophrenia, was analyzed.

METHODS

The PPAR/RXR family genes were screened by exploiting molecular inversion probe (MIP)-based targeted next-generation sequencing (NGS) using the samples of 1,200 Japanese patients with schizophrenia. The results were compared with the whole-genome sequencing databases of the Japanese cohort (ToMMo) and the gnomAD. To reveal the relationship between PPAR/RXR dysfunction and schizophrenia, Ppara KO mice and fenofibrate (a clinically used PPARα agonist)-administered mice were assessed by performing behavioral, histological, and RNA-seq analyses.

FINDINGS

Our findings indicate that c.209-2delA, His117Gln, Arg141Cys, and Arg226Trp of the PPARA gene are risk variants for schizophrenia. The c.209-2delA variant generated a premature termination codon. The three missense variants significantly decreased the activity of PPARα as a transcription factor in vitro. The Ppara KO mice exhibited schizophrenia-relevant phenotypes, including behavioral deficits and impaired synaptogenesis in the cerebral cortex. Oral administration of fenofibrate alleviated spine pathology induced by phencyclidine, an N-methyl-d-aspartate (NMDA) receptor antagonist. Furthermore, pre-treatment with fenofibrate suppressed the sensitivity of mice to another NMDA receptor antagonist, MK-801. RNA-seq analysis revealed that PPARα regulates the expression of synaptogenesis signaling pathway-related genes.

INTERPRETATION

The findings of this study indicate that the mechanisms underlying schizophrenia pathogenesis involve PPARα-regulated transcriptional machinery and modulation of synapse physiology. Hence, PPARα can serve as a novel therapeutic target for schizophrenia.

Refinement of coding SNPs in the human aryl hydrocarbon receptor gene using ISNPranker: An integrative-SNP ranking web-tool

Different bioinformatic methods apply various approaches to predict how much the effect of a SNP could be deleterious and therefore their results may differ significantly. However, variation studies often need to consider an integrated prediction result to analyze the effect of SNPs. To address this problem, we used an algorithm to map ordinal predictions to a numeral space and averaging them, and based on it we developed the ISNPranker web-tool (http://isnpranker.semilab.ir/). It takes heterogonous outputs of different predictors and generates integrated numerical predictions and ranks SNPs based on them. Afterward, we used ISNPranker to identify the most deleterious coding SNPs (cSNPs) of the human aryl hydrocarbon receptor (AHR) gene. AHR is a ligand-activated transcription factor that governs many molecular and cellular mechanisms and cSNPs may affect its structure, interactions, and function. Forty validated cSNPs of AHR were initially analyzed using 16 publicly available SNP analyzers and the results were introduced to the ISNPranker and integrated predictions were obtained. The cSNPs were ranked in 34 levels of danger and rs200257782 in the ARNT dimerization domain (ADD_121-289) of AHR was identified as the most deleterious cSNP. The rs148360742, which affect ADD_40-79 and Hsp90 binding domain (HBD_27-79) was in the second rank and the third and fourth ranks were occupied by ADD_121-289-located variations rs571123681 and rs141667112 respectively. In conclusion, we introduced ISNPranker, which is a web-tool for integrative ranking of SNPs, and we showed that AHR structure and function may be highly sensitive to the cSNPs in the ARNT dimerization domain.

Comprehensive in silico mutational-sensitivity analysis of PTEN establishes signature regions implicated in pathogenesis of Autism Spectrum Disorders

An extensively studied cancer and Autism Spectrum Disorders (ASD) gene like PTEN provided an exclusive opportunity to map its mutational-landscape, compare and establish plausible genotypic predictors of ASD-associated phenotypic outcomes. Our exhaustive in silico analysis on 4252 SNPs using >30 tools identified increased mutational-density in exon7. Phosphatase domain, although evolutionarily conserved, had the most nsSNPs localised within signature regions. The evolutionarily variable C-terminal side contained the highest truncating-SNPs outside signature regions of C2 domain and most PTMs within C-tail site which displayed maximum intolerance to polymorphisms, and permitted benign but destabilising nsSNPs that enhanced its intrinsically-disordered nature. ASD-associated SNPs localised within ATP-binding motifs and Nuclear-Localising-Sequences were the most potent triggers of ASD manifestation. These, along with variations within P, WPD and TI loops, M1 within phosphatase domain, M2 and MoRFs of C2 domain, caused severe long-range conformational fluctuations altering PTEN's dynamic stability- not observed in variations outside signature regions. 3'UTR-SNPs affected 44 strong miRNA brain-specific targets; several 5' UTR-SNPs targeted transcription-factor POLR2A and 10 pathogenic Splice-Affecting-Variants were identified.

Translational Diagnostics: An In-House Pipeline to Validate Genetic Variants in Children with Undiagnosed and Rare Diseases

Diagnosis is essential for the management and treatment of patients with rare diseases. In a group of patients, the genetic study identifies variants of uncertain significance or inconsistent with the phenotype; therefore, it is urgent to develop novel strategies to reach the definitive diagnosis. Herein, we develop the in-house Translational Diagnostics Program (TDP) to validate genetic variants as part of the diagnostic process with the close collaboration of physicians, clinical scientists, and research scientists. The first 7 of 33 consecutive patients for whom exome-based tests were not diagnostic were investigated. The TDP pipeline includes four steps: (i) phenotype assessment, (ii) literature review and prediction of in silico pathogenicity, (iii) experimental functional studies, and (iv) diagnostic decision-making. Re-evaluation of the phenotype and re-analysis of the exome allowed the diagnosis in one patient. In the remaining patients, the studies included either cDNA cloning or PCR-amplified genomic DNA, or the use of patients' fibroblasts. A comparative computational analysis of confocal microscopy images and studies related to the protein function was performed. In five of these six patients, evidence of pathogenicity of the genetic variant was found, which was validated by physicians. The current research demonstrates the feasibility of the TDP to support and resolve intramural medical problems when the clinical significance of the patient variant is unknown or inconsistent with the phenotype.

In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review

Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.

Investigating the structural impacts of a novel missense variant identified with whole exome sequencing in an Egyptian patient with propionic acidemia

Propionic Acidemia (PA) is an inborn error of metabolism caused by variants in the PCCA or PCCB genes, leading to mitochondrial accumulation of propionyl-CoA and its by-products. Here, we report a 2 year-old Egyptian boy with PA who was born to consanguineous parents. Biochemical analysis was performed using tandem mass spectrometry (MS/MS) on the patient's dried blood spots (DBS) followed by urine examination of amino acids using gas chromatography/mass spectrometry (GC/MS). Molecular genetic analysis was carried out using whole-exome sequencing (WES). The PCCA gene sequencing revealed a novel homozygous missense variant affecting the locus (chr13:100962160) of exon 16 of the PCCA gene, resulting in the substitution of the amino acid arginine with proline at site 476 (p.Arg476Pro). Computational analysis revealed that the novel variant might be pathogenic and attributed to decrease the stability and also has an effect on the biotin carboxylase c-terminal domain of the propionyl carboxylase enzyme. The physicochemical properties analysis using NCBI amino acid explorer study revealed restrictions in the side chain and loss of hydrogen bonds due to the variant. On the structural level, the loss of beta-sheet was observed due to the variant proline, which has further led to the loss of surrounding interactions. This loss of beta-sheet and the surrounding interactions might serve the purpose of the structural stability changes. The current study demonstrates that a combination of whole-exome sequencing (WES) and computational analysis are potent tools for validation of diagnosis and classification of disease-causing variants.

Accurate and efficient structure-based computational mutagenesis for modeling fluorescence levels of Aequorea victoria green fluorescent protein mutants

A computational mutagenesis technique was used to characterize the structural effects associated with over 46 000 single and multiple amino acid variants of Aequorea victoria green fluorescent protein (GFP), whose functional effects (fluorescence levels) were recently measured by experimental researchers. For each GFP mutant, the approach generated a single score reflecting the overall change in sequence-structure compatibility relative to native GFP, as well as a vector of environmental perturbation (EP) scores characterizing the impact at all GFP residue positions. A significant GFP structure–function relationship (P < 0.0001) was elucidated by comparing the sequence-structure compatibility scores with the functional data. Next, the computed vectors for GFP mutants were used to train predictive models of fluorescence by implementing random forest (RF) classification and tree regression machine learning algorithms. Classification performance reached 0.93 for sensitivity, 0.91 for precision and 0.90 for balanced accuracy, and regression models led to Pearson’s correlation as high as r = 0.83 between experimental and predicted GFP mutant fluorescence. An RF model trained on a subset of over 1000 experimental single residue GFP mutants with measured fluorescence was used for predicting the 3300 remaining unstudied single residue mutants, with results complementing known GFP biochemical and biophysical properties. In addition, models trained on the subset of experimental GFP mutants harboring multiple residue replacements successfully predicted fluorescence of the single residue GFP mutants. The models developed for this study were accurate and efficient, and their predictions outperformed those of several related state-of-the-art methods.

Structure-based functional analysis of BRCA1 RING domain variants: Concordance of computational mutagenesis, experimental assay, and clinical data

A significant impediment to the improvement of clinical outcomes in treating breast and ovarian cancers rests with the lack of available interpretations for BRCA1 variants of unknown significance. Two research groups recently implemented large-scale functional assays for quantifying effects of single missense mutations on homology-directed DNA repair activity of BRCA1 variants, which is critical for tumor suppression and strongly correlates with cancer risk, and their results are significantly concordant with each other as well as with known pathogenic and benign variant clinical data. In this work, we implemented an established computational mutagenesis procedure to characterize structural impacts of single residue replacements to the BRCA1 RING domain. The computational data showed similarly strong concordance with known clinical data as well as with experimental data from both functional assays. Predictions made by models trained on our computational data offer a complementary and orthogonal approach for classifying all remaining unexplored BRCA1 RING domain variants.

Informing patients about their mutation tests: CDKN2A c.256G>A in melanoma as an example

Background

When germline mutations are suspected as causal in cancer, patient DNA may be sequenced to detect variants in relevant genes. If a particular mutation has not been reported in reliable family studies, genetic counselors are facing a dilemma of appropriately informing patients. Many sequencing facilities provide an interpretation of the findings based on the available sequence databases or on prediction tools that are curated from bioinformatics and mechanistic datasets. The counseling dilemma is exacerbated if the pedigree data are not informative but the in silico predictions suggest pathogenicity.

Methods

We present here a real world example of the c.256G > A CDKN2A variant, which was detected in one melanoma patient where two siblings were diagnosed with melanoma in situ. We investigated a detailed family history of the affected siblings in order to survey probability of the cancer risks within the context to this mutation.

Results

This c.256G > A CDKN2A variant was detected in one of the brothers and in the melanoma-free mother while the other brother in the family tested negative. The variant had been previously described in one patient from a melanoma family. In the family under investigation, the mother’s 16 first-and second-degree relatives had survived past the median onset age for melanoma and none presented melanoma. We tested the variant using multiple bioinformatic tools that all predicted deleteriousness of the variant. The genetic counseling report to the melanoma patient stated that the CDKN2A variant was ‘likely pathogenic’ and the disease was defined as ‘likely hereditary melanoma’.

Conclusions

The pedigree data showed at the most a low penetrance variant, which, if taken into consideration, might have altered the provided diagnosis. When dealing with ‘practically’ unknown variants the counselors would be advised to incorporate a detailed family history rather than basing predictions on functionality provided by sequencing facilities.

In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome

Hyperparathyroidism-Jaw Tumor (HPT-JT) is an autosomal dominant disorder with variable expression, with an estimated prevalence of 6.7 per 1,000 population. Genetic testing for predisposing CDC73 (HRPT2) mutations has been an important clinical advance, aimed at early detection and/or treatment to prevent advanced disease. The aim of this study is to assess the most deleterious SNPs mutations on CDC73 gene and to predict their influence on the functional and structural levels using different bioinformatics tools. Method: Computational analysis using twelve different in-silico tools including SIFT, PROVEAN, PolyPhen-2, SNAP2, PhD-SNP, SNPs&GO, P-Mut, I-Mutant ,Project Hope, Chimera, COSMIC and dbSNP Short Genetic Variations were used to identify the impact of mutations in CDC73 gene that might be causing jaw tumor. Results: From (733) SNPs identified in the CDC73 gene we found that only Eleven SNPs (G49C, L63P, L64P, D90H, R222G, W231R, P360S, R441C, R441H, R504S and R504H) has deleterious effect on the function and structure of protein and expected to cause the syndrome. Conclusion: Eleven substantial genetic/molecular aberrations in CDC73 gene identified that could serve as diagnostic markers for hyperparathyroidism-jaw tumor (HPT-JT).

CYP2R1 and CYP27A1 genes: An in silico approach to identify the deleterious mutations, impact on structure and their differential expression in disease conditions

Mutations in CYP2R1 and CYP27A1 involved in the conversion of Cholecalciferol into Calcidiol were associated with the impaired 25-hydroxylase activity therefore affecting the Vitamin D metabolism. Hence, this study attempted to understand the influence of genetic variations at the sequence and structural level via computational approach. The non-synonymous mutations retrieved from dbSNP database were assessed for their pathogenicity, stability as well as conservancy using various computational tools. The above analysis predicted 11/260 and 35/489 non-synonymous mutations to be deleterious in CYP2R1 and CYP27A1 genes respectively. Native and mutant forms of the corresponding proteins were modeled. Further, interacting native and mutant proteins with cholecalciferol showed difference in hydrogen bonds, hydrophobic bonds and their binding affinities suggesting the possible influence of these mutations in their function. Also, expression of these genes in various disease conditions was investigated using GEO datasets which predicted that there is a differential expression in cancer and arthritis.

YARS2 Missense Variant in Belgian Shepherd Dogs with Cardiomyopathy and Juvenile Mortality

Dog puppy loss by the age of six to eight weeks after normal development is relatively uncommon. Necropsy findings in two spontaneously deceased Belgian Shepherd puppies indicated an abnormal accumulation of material in several organs. A third deceased puppy exhibited mild signs of an inflammation in the central nervous system and an enteritis. The puppies were closely related, raising the suspicion of a genetic cause. Pedigree analysis suggested a monogenic autosomal recessive inheritance. Combined linkage and homozygosity mapping assigned the most likely position of a potential genetic defect to 13 genome segments totaling 82 Mb. The genome of an affected puppy was sequenced and compared to 645 control genomes. Three private protein changing variants were found in the linked and homozygous regions. Targeted genotyping in 96 Belgian Shepherd dogs excluded two of these variants. The remaining variant, YARS2:1054G>A or p.Glu352Lys, was perfectly associated with the phenotype in a cohort of 474 Belgian Shepherd dogs. YARS2 encodes the mitochondrial tyrosyl-tRNA synthetase 2 and the predicted amino acid change replaces a negatively charged and evolutionary conserved glutamate at the surface of the tRNA binding domain of YARS2 with a positively charged lysine. Human patients with loss-of-function variants in YARS2 suffer from myopathy, lactic acidosis, and sideroblastic anemia 2, a disease with clinical similarities to the phenotype of the studied dogs. The carrier frequency was 27.2% in the tested Belgian Shepherd dogs. Our data suggest YARS2:1054G>A as the candidate causative variant for the observed juvenile mortality.

Customised next-generation sequencing multigene panel to screen a large cohort of individuals with chromatin-related disorder

BACKGROUND

The regulation of the chromatin state by epigenetic mechanisms plays a central role in gene expression, cell function, and maintenance of cell identity. Hereditary disorders of chromatin regulation are a group of conditions caused by abnormalities of the various components of the epigenetic machinery, namely writers, erasers, readers, and chromatin remodelers. Although neurological dysfunction is almost ubiquitous in these disorders, the constellation of additional features characterizing many of these genes and the emerging clinical overlap among them indicate the existence of a community of syndromes. The introduction of high-throughput next generation sequencing (NGS) methods for testing multiple genes simultaneously is a logical step for the implementation of diagnostics of these disorders.

METHODS

We screened a heterogeneous cohort of 263 index patients by an NGS-targeted panel, containing 68 genes associated with more than 40 OMIM entries affecting chromatin function.

RESULTS

This strategy allowed us to identify clinically relevant variants in 87 patients (32%), including 30 for which an alternative clinical diagnosis was proposed after sequencing analysis and clinical re-evaluation.

CONCLUSION

Our findings indicate that this approach is effective not only in disorders with locus heterogeneity, but also in order to anticipate unexpected misdiagnoses due to clinical overlap among cognate disorders. Finally, this work highlights the utility of a prompt diagnosis in such a clinically and genetically heterogeneous group of disorders that we propose to group under the umbrella term of chromatinopathies.

In silico analysis of non-synonymous single nucleotide polymorphisms (nsSNPs) in the human GJA3 gene associated with congenital cataract

BACKGROUND

Gap junction protein alpha 3 (GJA3), an important pathogenic gene of congenital cataracts, encodes the transmembrane protein connexin46, which functions as an intercellular channel for voltage and chemical gating by forming dodecamers. This study systematically collected nsSNP information for the GJA3 gene from SNP databases and literature and screened for nsSNPs with high risks of pathogenicity.

RESULTS

A total of 379 nsSNPs of GJA3 were identified. A total of 88 high-risk pathogenic GJA3 nsSNPs were found, including 31 published nsSNPs associated with congenital cataracts and 57 novel nsSNPs predicted by all eight online tools. The 88 high-risk pathogenic mutations, which are related to 67 amino acids in the wild-type sequences, cause a decrease in protein stability according to I-Mutant 3.0, MUpro and INPS. G2 and R33 were predicted to participate in post-translational modification and ligand binding by ModPred, RaptorX Binding and COACH. Additionally, high-risk mutations were likely to involve highly conserved sites, random coils, alpha helixes, and extracellular loops and were accompanied by changes in amino acid size, charge, hydrophobicity and spatial structure.

CONCLUSIONS

Eighty-eight high-risk pathogenic nsSNPs of GJA3 were screened out in the study, 57 of which were newly reported. The combination of multiple in silico tools is highly efficient for targeting pathogenic sites.

Expanding the clinical and neuroimaging features of NKX6-2-related hereditary spastic ataxia type 8

Pathogenic variants in NKX6-2 gene causing autosomal recessive spastic ataxia type 8 with hypomyelinating leukodystrophy have been reported in few families around the world. In this study, we performed Whole Exome Sequencing and identified a novel missense variant, c.501C > G; p.(Phe167Leu), in two affected siblings with main manifestations of global developmental delay, motor regression, hypotonia, clonus in lower limbs and muscle bulk atrophy especially in the upper limbs, spasticity and contracture, scoliosis, hip dislocation, oculomotor apraxia, horizontal and vertical nystagmus. In addition, wrist and foot drop due to peripheral axonal neuropathy were observed in these patients as a new clinical finding and cerebellar white matter involvement in brain Magnetic Resonance Imaging (MRI) as new imaging finding. Therefore, we expanded the manifestations of NKX6-2-related disorders in this manuscript.

Computational analyses prioritize and reveal the deleterious nsSNPs in human angiotensinogen gene

Angiotensinogen (AGT) is a key component of renin-angiotensin-aldosterone system (RAAS), which plays central role in blood pressure homeostasis. Association of AGT polymorphisms have been investigated in different ethnic populations in variety of cardiovascular and non-cardiovascular conditions. In this study, 354 non-synonymous SNPs (nsSNPs) of AGT were evaluated to predict damaging and structurally important variants. Majority of the deleterious nsSNPs occurred in the evolutionary conserved regions. Several of these nsSNPs were found to affect post-translational modifications like methylation, glycosylation, phosphorylation, ubiquitination etc. Structural evaluations predicted 19 variants as destabilizing and some of them were also predicted to destabilize the renin-AGT interaction. Therefore, the present computational investigation predicted pathogenic and functionally important variants of human AGT gene. The study has also shown that AGT deregulation is associated with survival outcome in patients with gastric and breast cancer, using microarray gene expression profile. Furthermore, the computationally screened nsSNPs can be analyzed in population based genotyping studies and may help futuristic drug development in the area of AGT pharmacogenomics.

Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning

Next-generation sequencing methods have not only allowed an understanding of genome sequence variation during the evolution of organisms but have also provided invaluable information about genetic variants in inherited disease and the emergence of resistance to drugs in cancers and infectious disease. A challenge is to distinguish mutations that are drivers of disease or drug resistance, from passengers that are neutral or even selectively advantageous to the organism. This requires an understanding of impacts of missense mutations in gene expression and regulation, and on the disruption of protein function by modulating protein stability or disturbing interactions with proteins, nucleic acids, small molecule ligands, and other biological molecules. Experimental approaches to understanding differences between wild-type and mutant proteins are most accurate but are also time-consuming and costly. Computational tools used to predict the impacts of mutations can provide useful information more quickly. Here, we focus on two widely used structure-based approaches, originally developed in the Blundell lab: site-directed mutator (SDM), a statistical approach to analyze amino acid substitutions, and mutation cutoff scanning matrix (mCSM), which uses graph-based signatures to represent the wild-type structural environment and machine learning to predict the effect of mutations on protein stability. Here, we describe DUET that uses machine learning to combine the two approaches. We discuss briefly the development of mCSM for understanding the impacts of mutations on interfaces with other proteins, nucleic acids, and ligands, and we exemplify the wide application of these approaches to understand human genetic disorders and drug resistance mutations relevant to cancer and mycobacterial infections. STATEMENT FOR A BROADER AUDIENCE: Genetic or somatic changes in genes can lead to mutations in human proteins, which give rise to genetic disorders or cancer, or to genes of pathogens leading to drug resistance. Computer software described here, using statistical approaches or machine learning, uses the information from genome sequencing of humans and pathogens, together with experimental or modeled 3D structures of gene products, the proteins, to predict impacts of mutations in genetic disease, cancer and drug resistance.

Understanding the histogenesis of a HRAS-PIK3R1 co-driven metastatic metaplastic breast carcinoma associated with squamous metaplasia of lactiferous ducts

Metaplastic breast carcinoma (MBC) represents a heterogeneous group of aggressive primary breast cancers that can show differentiation into carcinomatous and sarcomatous elements. Due to its rapid growth, this malignancy can replace precursor lesions, which remain unknown in most cases. Herein, we describe a MBC presenting as a deceptive post-biopsy hematoma. Histopathological and immunohistochemical evaluation of the primary tumor revealed a squamous cell carcinoma arising in a background of squamous metaplasia of lactiferous ducts (SMOLD). In the absence of ductal carcinoma in situ, we consider SMOLD as a nonobligatory precursor of MBC. The tumor showed 'dedifferentiation' into spindle, mucin-producing, osteoclast-like giant cell and fibromatosis-like carcinoma. Next-generation sequencing revealed the driver mutations HRAS^Q61R and PIK3R1^{c.1738_1745+2del} in addition to MYH11^S638L and amplification of ERCC5 and FGF14, which were potential contributors to tumor phenotype. Tumor dedifferentiation was probably facilitated by epithelial-to-mesenchymal transition (EMT) with aberrant expression of platelet and endothelial adhesion molecule-1, leading to early metastasis via hematogenous route rather than lymphatic. The co-occurrence of phosphoinositide 3-kinase and mitogen-activated protein kinase pathway abnormalities along with EMT could mediate divergent growth in breast cancer.

Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when

The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.

Glycogen storage diseases: Twenty-seven new variants in a cohort of 125 patients

BACKGROUND

Hepatic glycogen storage diseases (GSDs) are a group of rare genetic disorders in which glycogen cannot be metabolized to glucose in the liver because of enzyme deficiencies along the glycogenolytic pathway. GSDs are well-recognized diseases that can occur without the full spectrum, and with overlapping in symptoms.

METHODS

We analyzed a cohort of 125 patients with suspected hepatic GSD through a next-generation sequencing (NGS) gene panel in Ion Torrent platform. New variants were analyzed by pathogenicity prediction tools.

RESULTS

Twenty-seven new variants predicted as pathogenic were found between 63 variants identified. The most frequent GSD was type Ia (n = 53), followed by Ib (n = 23). The most frequent variants were p.Arg83Cys (39 alleles) and p.Gln347* (14 alleles) in G6PC gene, and p.Leu348Valfs (21 alleles) in SLC37A4 gene.

CONCLUSIONS

The study presents the largest cohort ever analyzed in Brazilian patients with hepatic glycogenosis. We determined the clinical utility of NGS for diagnosis. The molecular diagnosis of hepatic GSDs enables the characterization of diseases with similar clinical symptoms, avoiding hepatic biopsy and having faster results.

In Silico Genetics Revealing 5 Mutations in CEBPA Gene Associated With Acute Myeloid Leukemia

Background:

Acute myeloid leukemia (AML) is an extremely heterogeneous malignant disorder; AML has been reported as one of the main causes of death in children. The objective of this work was to classify the most deleterious mutation in CCAAT/enhancer-binding protein-alpha (CEBPA) and to predict their influence on the functional, structural, and expression levels by various Bioinformatics analysis tools.

Methods:

The single nucleotide polymorphisms (SNPs) were claimed from the National Center for Biotechnology Information (NCBI) database and then submitted into various functional analysis tools, which were done to predict the influence of each SNP, followed by structural analysis of modeled protein followed by predicting the mutation effect on energy stability; the most damaging mutations were chosen for additional investigation by Mutation3D, Project hope, ConSurf, BioEdit, and UCSF Chimera tools.

Results:

A total of 5 mutations out of 248 were likely to be responsible for the structural and functional variations in CEBPA protein, whereas in the 3′-untranslated region (3′-UTR) the result showed that among 350 SNPs in the 3′-UTR of CEBPA gene, about 11 SNPs were predicted. Among these 11 SNPs, 65 alleles disrupted a conserved miRNA site and 22 derived alleles created a new site of miRNA.

Conclusions:

In this study, the impact of functional mutations in the CEBPA gene was investigated through different bioinformatics analysis techniques, which determined that R339W, R288P, N292S, N292T, and D63N are pathogenic mutations that have a possible functional and structural influence, therefore, could be used as genetic biomarkers and may assist in genetic studies with a special consideration of the large heterogeneity of AML.

VIPdb, a genetic Variant Impact Predictor Database

Genome sequencing identifies vast number of genetic variants. Predicting these variants' molecular and clinical effects is one of the preeminent challenges in human genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information is conveyed to molecular and cellular functions, and is an essential step towards precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We summarize these tools as well as their characteristics, in the genetic Variant Impact Predictor Database (VIPdb). This database will help researchers and clinicians explore appropriate tools, and inform the development of improved methods. VIPdb can be browsed and downloaded at https://genomeinterpretation.org/vipdb.

From genomic variation to protein aberration: Mutational analysis of single nucleotide polymorphism present in ULBP6 gene and implication in immune response

BACKGROUND

Genetic polymorphisms have been identified as one of the underlying factors in disease pathogenesis and drug resistance since they account for protein dysfunctionality, or in some cases, aberrancy. This explains the high degree of inactivity that characterizes the polymorphic variants of ULBP6 binding protein, which in turn disrupts its primary interaction with human Natural Killer Group 2-member D (NKG2D) and accounts for an impediment to immuno-surveillance. The possible identification of deleterious non-synonymous Single Nucleotide Polymorphisms (nsSNPs) present in the ULBP6 gene is essential for the development of novel gene therapies to prevent the translation of dysfunctional protein variants.

METHODS/RESULTS

In this study, for the first time, we employed an SNP-informatics approach (SNPs retrieval, pathogenic/mutational analysis, phenotypic analysis, and structural analysis) and molecular dynamics techniques to identify and characterize undesirable SNPs coupled with their impact on ULBP6 structural activities relative to dysfunctionality. V52F was predictively pathogenic amongst SNPs studied. Conformational and dynamic studies revealed that in comparison to wildtype ULBP6 (ULBP6^wt), pathogenic ULBP6^V52F demonstrated considerable structural inactivity, which could, in turn, impede biological protein-protein interactions. Moreover, ULBP6^V52F showed relatively limited motions in the conformational space as deduced from estimations of structural stability, fluctuations, and principal components.

CONCLUSION

This study provides a workable paradigm for investigating pathological nsSNPS using computational platforms which findings present ULBP6^V52F as a novel and attractive immunotherapeutic target in combatting immune-associated disorders.

Novel Deleterious nsSNPs within MEFV Gene that Could Be Used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using Bioinformatics Analysis

Background

Familial Mediterranean Fever (FMF) is the most common autoinflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin. We aimed to identify the pathogenic SNPs in MEFV by computational analysis software.

Methods

We carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function.

Result

23 novel mutations out of 857 nsSNPs are found to have deleterious effect on the MEFV structure and function.

Conclusion

This is the first in silico analysis of MEFV gene to prioritize SNPs for further genetic mapping studies. After using multiple bioinformatics tools to compare and rely on the results predicted, we found 23 novel mutations that may cause FMF disease and it could be used as diagnostic markers for Mediterranean basin populations.

A novel ISCA2 variant responsible for an early-onset neurodegenerative mitochondrial disorder: a case report of multiple mitochondrial dysfunctions syndrome 4

BACKGROUND

Multiple Mitochondrial Dysfunctions Syndrome 4 (MMDS4) is manifested as a result of ISCA2 mutations. ISCA2 is a vital component of 4Fe-4S clusters assembly machine. Therefore, in MMDS4 patients, deficient mitochondrial respiratory chain complexes I and II, Aconitase and Succinate dehydrogenase of Kerbs cycle and Lipoic Acid Synthetase in the biosynthesis of lipoic acid are expected.

CASE PRESENTATIONS

A 7 months boy in an Iranian consanguineous family with progressive neurodegenerative problems was referred to us. Primarily, general laboratory tests, Abdomen ultrasonography and brain magnetic resonance imaging were performed. In order to find out the genetic problem in this case Whole Exome Sequencing (WES) following by Sanger sequencing was carried out. A novel variant (c.355G > A, p.Ala119Thr) in ISCA2 gene was identified by WES in the proband. Confirmation and segregation in the family for this variant was performed by Sanger sequencing. In-Silico prediction of the ISCA2 secondary structure showed that a helix motif in the Fe-S biosynthesis domain of ISCA2 protein will be eliminated as a result of this variant.

CONCLUSIONS

We reported the first patient with ISCA2 variant in Iranian population and the third one in the world reported for ISCA2 gene, so far associated with early-onset mitochondrial neurodegeneration. However further functional studies on this variant or finding it in other patients with similar clinical problems are needed to confirm the pathogenicity of this variant.

BRCA1- and BRCA2-specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge

BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene-specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.